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<p>Contains classes and functionality for computation nodes in a neural network or computational graph.  
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Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_add_node.html">AddNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a node that performs element-wise addition between two input tensors.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_add_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_e_l_u_node.html">ELUNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents an Exponential Linear Unit (ELU) activation function node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_e_l_u_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_hard_sigmoid_node.html">HardSigmoidNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Hard Sigmoid activation function node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_hard_sigmoid_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_hard_swish_node.html">HardSwishNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Hard Swish activation function node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_hard_swish_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_leaky_re_l_u_node.html">LeakyReLUNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Leaky Rectified Linear Unit (LeakyReLU) activation function node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_leaky_re_l_u_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_mat_mul_node.html">MatMulNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a matrix multiplication operation node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_mat_mul_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_re_l_u_node.html">ReLUNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Rectified Linear Unit (ReLU) operation node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_re_l_u_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_add_node.html">ScalarAddNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a scalar addition operation node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_add_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_div_node.html">ScalarDivNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a scalar division operation node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_div_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_mul_node.html">ScalarMulNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a scalar multiplication operation node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_mul_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_sub_node.html">ScalarSubNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a scalar subtraction operation node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_sub_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_sigmoid_node.html">SigmoidNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Sigmoid activation function node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_sigmoid_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_softmax_node.html">SoftmaxNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Implements the Softmax activation function as a node in a neural network computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_softmax_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_sub_node.html">SubNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a subtraction operation node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_sub_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_swish_node.html">SwishNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Swish activation function node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_swish_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_tanh_node.html">TanhNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a hyperbolic tangent (tanh) activation function node in a computational graph.  <a href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_tanh_node.html#details">More...</a><br /></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Contains classes and functionality for computation nodes in a neural network or computational graph. </p>
<p>The <code><a class="el" href="namespace_neu_zephyr_1_1_nodes_1_1_computation.html" title="Contains classes and functionality for computation nodes in a neural network or computational graph.">NeuZephyr::Nodes::Computation</a></code> namespace provides a collection of classes that represent various computational operations within a neural network. These nodes perform essential mathematical operations during the forward pass in a computational graph.</p>
<p>This namespace includes:</p><ul>
<li><b><a class="el" href="namespace_neu_zephyr_1_1_nodes_1_1_computation.html" title="Contains classes and functionality for computation nodes in a neural network or computational graph.">Computation</a> <a class="el" href="namespace_neu_zephyr_1_1_nodes.html" title="Contains classes and functionality for nodes in a neural network or computational graph.">Nodes</a></b>: <a class="el" href="namespace_neu_zephyr_1_1_nodes.html" title="Contains classes and functionality for nodes in a neural network or computational graph.">Nodes</a> responsible for performing mathematical operations and data transformations such as activation functions, matrix operations, and normalization techniques.<ul>
<li><b>Activation Functions</b>: <a class="el" href="namespace_neu_zephyr_1_1_nodes.html" title="Contains classes and functionality for nodes in a neural network or computational graph.">Nodes</a> such as <code><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_re_l_u_node.html" title="Represents a Rectified Linear Unit (ReLU) operation node in a computational graph.">ReLUNode</a></code>, <code><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_sigmoid_node.html" title="Represents a Sigmoid activation function node in a computational graph.">SigmoidNode</a></code>, <code><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_tanh_node.html" title="Represents a hyperbolic tangent (tanh) activation function node in a computational graph.">TanhNode</a></code>, <code><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_leaky_re_l_u_node.html" title="Represents a Leaky Rectified Linear Unit (LeakyReLU) activation function node in a computational grap...">LeakyReLUNode</a></code>, etc., which apply non-linear transformations to the input data.</li>
<li><b>Mathematical Operations</b>: <a class="el" href="namespace_neu_zephyr_1_1_nodes.html" title="Contains classes and functionality for nodes in a neural network or computational graph.">Nodes</a> like <code><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_add_node.html" title="Represents a node that performs element-wise addition between two input tensors.">AddNode</a></code>, <code><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_mat_mul_node.html" title="Represents a matrix multiplication operation node in a computational graph.">MatMulNode</a></code>, <code><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_mul_node.html" title="Represents a scalar multiplication operation node in a computational graph.">ScalarMulNode</a></code>, <code><a class="el" href="class_neu_zephyr_1_1_nodes_1_1_computation_1_1_scalar_div_node.html" title="Represents a scalar division operation node in a computational graph.">ScalarDivNode</a></code>, and others for performing basic arithmetic and matrix operations.</li>
</ul>
</li>
</ul>
<p>The nodes in this namespace interact with <code>Tensor</code> objects, performing data manipulation operations necessary for building neural network layers and facilitating the forward propagation of information through the network.</p>
<dl class="section note"><dt>Note</dt><dd><ul>
<li>The nodes in this namespace are intended for mathematical and computational operations in the forward pass.</li>
<li>These nodes can be combined with other nodes to form complex neural network architectures.</li>
<li>Make sure to manage memory properly when working with large tensors, particularly when leveraging GPU resources.</li>
</ul>
</dd></dl>
<dl class="section author"><dt>Author</dt><dd>Mgepahmge (<a href="https://github.com/Mgepahmge">https://github.com/Mgepahmge</a>)</dd></dl>
<dl class="section date"><dt>Date</dt><dd>2024/11/29 </dd></dl>
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